Saturday, October 10, 2020

Deepfakes: "Disinformed"

A topic of abiding interest.

From Inference Review:

There have been fakes as long as there have been frauds, and that is a very long time; but deepfakes are new fakes, and having initially loitered along the margins of general awareness, they are now occupied in haunting it. Tens of thousands of deepfakes have already been created. The technical means of fiddling with images is hardly new. Standing beside Joseph Stalin in one photograph taken along the newly completed White Sea Canal, Nikolai Yezhov disappeared from the very same photograph some months later, as he, in fact, had disappeared from life. The fakery is fine, but it is no better than that, the ensuing photograph visually unbalanced by a lot of gray canal water where Yezhov had once stood. It is thanks to a technology invented in 2014 that deepfakery is capable of taking verisimilitude to a new level.

Generative Adversarial Networks

The ability to produce ever more persuasive deepfakes has been made possible by a recent form of machine learning called generative adversarial networks—or GANs. A GAN operator pits a generator (G) against a discriminator (D) in a gamelike environment in which G tries to fool D into incorrectly discriminating between fake and real data. The technology works by means of a series of incremental but rapid adjustments that allows D to discriminate data while G tries to fool it.

How fast are these adjustments? Very fast. A computer can play 24 trillion games of Texas Hold’em every second. To beat human opponents, a computer does not need to assess their strategies. It relies on the patterns it picks out, and assumes only that human strategy is limited to a few flexible tactics. DeepMind beat human players at 99.8% of StarCraft II games, a game subtler and more abstract than Texas Hold’em.

GAN technology is not particularly exotic; the software is available commercially, and anyone who can write code can figure out how to use it. If simply using it is open admission, what about using it to change the 2020 election? That, David Doermann argues, “would take a massive amount of computing power.” Rogue actors, he adds, are too small to do much. “A nation state is required.”1

What about an organized group scaled somewhere between a rogue actor and a rogue state?

It is too late to ban GANs. But it is possible to criminalize certain uses, and efforts are afoot to do so. Beyond the ambit of domestic law, legal remedies are less likely to be effective. GANs have any number of applications. Some are pure as the driven snow. GANs can reconstruct three-dimensional images from two-dimensional photographs. They can be used to visualize industrial design, improve astronomical images by filling in statistically what real cameras cannot capture, and generate showers of imaginary particles for high-energy physics experiments. GANs can also be used to visualize motion in static environments, which could help find people lost or hiding in forests or jungles. In 2016, GAN technology was used to generate new molecules for a variety of protein targets in cells implicated in fibrosis, inflammation, and cancer.2

So much for Dr. Jekyll. Mr. Hyde now follows. What makes GANs frightening is their power to produce photographic images of people who do not exist, or to generate video from voice recordings, or to doctor images of people who do exist to make them seem to be someone else, or to say things they never did or would say. GANs can be used to create pornography by using an image without the subject’s knowledge or consent. According to the company Sensity, formerly Deeptrace, of the 15,000 online deepfakes detected by September 2019, 96% were pornographic.3

GAN technology is intended to deceive.

And the technology is flexible. Those who mean mischief favor the adversarial neural network; those who do not, the discriminators. This allows authorities to better detect deepfake attacks; but it also makes them adept at offense if they themselves go rogue. Any formula that helps the defense can be used to improve an attack. In planting false positives, clever operators tag real videos as fakes. Ambiguity infects the entire informational domain.

Pornography aside, many other nefarious uses of deepfakery are obvious. In August 2019, the Wall Street Journal reported on the first big-money case of identity fraud.4 Scammers used voice-changing technology to impersonate a chief executive. The money is gone; they have not been caught. Business leaders or banking lenders can be made to say things that dupe investors and markets, the ensuing herd yielding millions for those in the know.

Political uses carry enormous potential. If Russian efforts got Donald Trump elected, as former Director of National Intelligence General James Clapper suggested, one could hardly think of a more ominous threat.5 A GAN-generated deepfake already exists of Nancy Pelosi sounding drunk and saying things she never said.6 It is primitive, and thus easy to detect, but that did not prevent both President Trump and Rudy Giuliani from retweeting it. The same principle was at work in recent deepfakes of political figures in Gabon and Malaysia.7 Social context critically determines the effect of technological tomfoolery. The fake alone need only go so far, and by the time a fake is found out, it may be too late to prevent an incensed or excited mob from violence.

Terrorism is often an attempt to lure a target into reacting in a way that undermines its own principles and sources of political legitimacy.8 ISIS and al-Qaeda both proved more technologically adept than was at first thought. These organizations could easily use GANs to assign to various national leaders speeches or sentiments that might incite riots from Karachi to Fez, as when Crown Prince Mohammed bin Salman, technologically refreshed and so reborn, claims that Saudi military forces, having secretly obtained three nuclear weapons from Pakistan, are preparing to bomb Tehran, Qom, and Bandar Abbas.

Will regional publics and governments believe it real? If not, what will they do?


Disinformation has been a part of espionage for centuries. What is new about deepfakery, then? For one thing, an illusion of reality more convincing than any produced in the past. For another, entirely new social and cultural contexts. The result is a vamping up of venerable means to satisfy modern goals. The Roman coliseum was useful for stirring up a mob by means of leather-lunged orators. Useful but limited. The advent of movable type? Better. Yet only a small minority ever gained literacy. The radio? Much better. Radio provided even the linen-lunged the power to reach mass audiences. Benito Mussolini’s regime was a pioneer in the 1920s. The Nazis soon followed, combining the use of radio with old-fashioned spectacle such as the Nuremberg rallies. Father Charles Coughlin used radio to dangerously good effect. The creation of the Federal Communications Commission in 1934 testified to the concern of US democratic elites.

Sound is one thing; sight is another. People believe their eyes before their ears. In 1984, something like artificial intelligence beamed Max Headroom to American viewers through their television sets. The technology was primitive, and Max was actually a man in facial prosthetics and a plastic suit. If his original purpose was entertainment, he was, at once, hijacked for political advocacy. On November 22, 1987, two Chicago television stations had their signal taken over by unknown individuals, one of whom wore a Max Headroom look-alike costume. The fake Max rambled on for about ninety seconds contemning the real Max’s commercial endorsements, and concluding with a pair of exposed buttocks being whacked by a fly swatter before normal programming resumed.

The culprits, it is gratifying to recount, were never apprehended, still less identified.

Graphic capabilities have now progressed from Max Headroom to computer-aided anime and CGI technologies—child’s play compared to GANs. The new technology requires sophisticated techniques all its own. Twitter works as well as it does by promoting an obvious sense of both immediacy and intimacy. There it is: the naked thought, shorn of layers, lawyers, fillers, or filters. To communicate to the American people, Trump prefers tweets to press conferences. Intimacy of this sort requires many individual technical platforms to be linked together. More than five billion people now have mobile devices, over half of them smartphones.9 The iPhone came on the market in June 2007 and took a decade to reach initial market saturation. This is a fast-moving development, and one with radical effects. If the Arab Spring was driven by young people, it was made possible by social media.10 A platform as anodyne as Facebook was sufficient to deepen, if not cause, ethnic cleansing in Myanmar.11 The country had recently emerged from a military dictatorship, and as the internet was relatively new, those incited to violence were not able to distinguish real information from false. They were not about to take any chances....



June 2019
Stephen Wolfram: "A Few Thoughts about Deep Fakes" (+ how to know what's real)
June 2018
AI: "Experts Bet on First Deepfakes Political Scandal" 

May 2018
"The US military is funding an effort to catch deepfakes and other AI trickery"
But, but...I saw it on the internet....
February 2018
"Talk down to Siri like she's a mere servant – your safety demands it"
The "mere" is troubling for some reason but it's CPI day so no time to reflect on why.... 

Related (and because all news is local), from the Columbia Journalism Review:

Reporting in a Machine Reality: Deepfakes, misinformation, and what journalists can do about them
That's not local in the geographical sense but rather intellectual provincialism:
...In yesterday's "Questions America Wants Answered: How Will Brexit Affect The Art Market?" I amused myself with the provincialism of the headline question, somewhat akin to the old joke about the small Italian town that sent its most esteemed resident, a tailor by trade, to represent said villaggio at an audience with the Pope. Upon his return from Rome the citizens crowded around and asked "What kind of man is Il Papa?

Their emissary replied, "About a 42 regular"....
We all see the world through our own self-created lenses. And on a related provincialism point, easily the most terrifying news of the last couple years:

"Equity Analysts Join the Gig Economy"
"The automation of creativity: scary but inevitable"
First they came for the journalists and I did not speak out-
Because I was not a journalist.

Then they came for the ad agency creatives and I did not speak out-
Because I was not an ad agency creative. (see below)

Then they came for the financial analysts and I
said 'hang on one effin minute'....